Pain Points
01
User inquiries are often colloquial, multi-intent, long, and filled with filler words, making intent hard to understand accurately.
Pain Points
02
Online agents struggle to confirm knowledge questions and business processes, and their wording is monotonous and overly AI-like.
Pain Points
03
New business and new policies are hard to find, responses are inconsistent, and clauses are vague. Documents need manual processing, while much historical marketing knowledge is outdated with no auto-update mechanism.
Based on historical conversations in private business scenarios, we fine-tune a dedicated intent model with manual annotation and data augmentation to better handle complex issues. An Agent + RAG architecture reduces hallucinations while balancing answer quality and latency.
Clean existing FAQ knowledge and build an end-to-end loop for FAQ creation and application, keeping FAQ knowledge timely and consistent.
Provide standard APIs and SDKs to connect existing customer service platforms such as apps, WeCom, and online service systems without replacing legacy systems, improving experience and efficiency.
First-contact resolution in complex online scenarios rises to over 95%, with no hallucinations.
Replaces a large amount of repetitive consultation, increases the number of customers each agent can manage by 35%, and improves customer satisfaction by 20%.
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About Us
Business Cooperation Email
Address
Floor 16, Fangzheng International Building, No. 52 Beisihuan West Road, Haidian District, Beijing, China.
© 2023, Langboat Co., Limited. All rights reserved.
Large Model Registration Code:Beijing-MengZiGPT-20231205
Business Cooperation:
bd@langboat.com
Address:
Floor 16, Fangzheng International Building, No. 52 Beisihuan West Road, Haidian District, Beijing, China.
Official Accounts:

© 2023, Langboat Co., Limited. All rights reserved.
Large Model Registration Code:Beijing-MengZiGPT-20231205